RNAMiner makes genetic science easier, could lead to faster results

Information technology rapidly is advancing the study of genetics and the search for causes of major diseases. Analysis of genomic sequences that once took days or months now can be performed in a matter of hours. Yet, for most genetic scientists, the lack of access to computer servers and programs capable of quickly handling vast amounts of data can hinder genetic advancements. Now, a group of scientists at the University of Missouri has introduced a game changer in the world of biological research. The online, free service, RNAMiner, has been developed to handle large datasets which could lead to faster results in the study of plant and animal genomics.

"This work actually started mainly because of the demand of MU scientists," said Jianlin Cheng, an associate professor of computer science in the MU College of Engineering. "RNA sequencing is the means by which researchers use modern sequencing techniques to study RNA, or ribonucleic acid. The process has increased the speed that can note the differences in gene expression among genomes--but it comes at a cost. Often, scientists must sift through incredibly large amounts of data to get to usable results. RNAMiner has cut that time drastically."

Cheng and doctoral students Jilong Li and Jie Hou partnered with members of the MU Center for Botanical Interaction Studies, the Division of Biological Sciences, the Department of Chemistry, the Department of Biochemistry, the MU Informatics Institute and the Bond Life Sciences Center to analyze vast genomic data sets and to formulate the design of RNAMiner.

The website was created to be user-friendly and allows users to upload data, analyze it through as many as five steps against the complete genomes of five species: human, mouse, Drosophila melanogaster (a type of fly), TAIR10 arabidopsis (a small flowering plant) and Clostridium perfringens (a type of bacterium). Genomic data for any species is welcome for upload to grow the database.

On average, two gigabytes of data takes approximately 10 hours for the servers to process and analyze. Most researchers get results within a couple of hours, Cheng said.

"To use our pipeline, you don't have to know about computing tools," Cheng said. "You just need to upload files and select several parameters, and it will automatically give those results. Using this raw data, we can compress that basically hundreds of thousands of times, even one million times, and make the connections needed for our collaborators to identify the genes that cause diseases or certain traits of plants and do some experiments to verify their findings."

New paper explores the strategies nature employs to achieve different mechanical functions

A spider's web is one of the most intricate constructions in nature, but its precious silk has more than one use. Silk threads can be used as draglines, guidelines, anchors, pheromonal trails, nest lining, or even food. And each use requires a slightly different type of silk, optimized for its function.

"Each type of silk has similar proteins, but they are synthesized differently," said Sinan Keten, assistant professor of mechanical and civil engineering at Northwestern University's McCormick School of Engineering. "Then the spider knows how fast to reel the silk to get different properties. Nature is smart. It can tailor a structure to get different mechanical properties."

Spider silk is one biological material that Keten discusses in his new paper "The role of mechanics in biological and bio-inspired systems," published in the July 6 issue of Nature Communications. Surveying everything from sea cucumbers and Venus flytraps to human muscles and trees, the review paper broadly explores the strategies that biology employs to create different functions and the mechanics at play within those functions. Discovering how and why biological systems attain desirable static and dynamic mechanical functionalities often reveals principles that inform new synthetic designs based on biological systems.

Coauthored by Philip LeDuc of Carnegie Mellon University, Keten's paper covers three themes: bottom-up assembly, multiscale and multiphasic organization, and the passive and active features found in different materials.

"We wanted to point out some of the overarching principles that many systems share," Keten said. "By understanding these and learning from biology, we can speed up discovery."

Much of the paper focuses on nanoconfinement, a major part of Keten's research. The term describes the ability to control the building blocks of a material at the smallest level in order to ensure specific properties. When a spider creates its dragline, for example, it spins silk faster than when its constructing a web. The crystals comprising the silk are smaller when it's spun faster, resulting in stronger material. When the crystals are larger, the silk is less structured and contains more defects.

Although Keten spent the early part of his career studying spider silk, he has more recently shifted his focus to cellulose in tree branches. "We see the same things in silk as we do wood," Keten said. "Small crystals are preferred to larger crystals. It call comes back to nanoconfinement, which is to make the material's building blocks small enough that you don't have defects and therefore get stronger features. Additionally, nanoscale building blocks give rise to more interfaces in materials where intriguing physical phenomena may emerge from the large surface of nanoparticles."

Funded by the Army Research Office, Keten's team discovered that, on the nanolevel, cellulose crystals are transparent and as tough as Kevlar. He suggests that these properties could be mimicked to develop bulletproof glass and goggles and uses supercomputation to explore the best ways to arrange the crystals to achieve different properties.

"You never mimic the biological system one-to-one," Keten said. "Like flight, for example. We can learn about aerodynamics from birds, but we don't design an airplane like a bird. That also applies to spider silk, which is a very tough and strong material. We don't use the exact same building blocks to develop a tough, man-made material. We use other building blocks but arrange them using the same methods we learn from biology."

When newborn babies open their eyes for the first time, they already possess nerve cells specialized in particular stimuli in the visual cortex of their brains - but these nerve cells are not systematically linked with each other. How do neural networks that react in a particular way to particular features of a stimulus develop over the course of time? In order to better understand the steps of this development and explain the complicated processes of reorganization they involve, an international team of researchers has now developed a supercomputer model that precisely simulates the biological processes. The results of the study by Prof. Dr. Stefan Rotter, Bernstein Center Freiburg (BCF) and Cluster of Excellence BrainLinks-BrainTools of the University of Freiburg, conducted in cooperation with Dr. Claudia Clopath from the Imperial College London, England, have now been published in the journals PLOS Computational Biology and PLOS ONE.

"Our model enabled us to achieve a meaningful combination of typical features of biological neural networks in animals and humans in a computer simulation for the first time ever," reports the neuroscientist Dr. Sadra Sadeh from the BCF. "The networks harness the principle of feedback to make nerve cells in the visual system into efficient detectors of features. In addition, they can precisely coordinate the points of contact between the cells - the synapses - in learning processes." It is difficult to combine these two properties in supercomputer models, because it can easily lead to an explosion of activity in the network - similar to an epileptic fit. To keep the activity in the network stable, the researchers integrated inhibitory synapses into the learning process, which control the excitation in the network.

Researchers can now use the supercomputer model to simulate various developmental processes in the brain's visual cortex. Among other things, it will allow them to determine how connections between the nerve cells change the first time they receive stimuli from both eyes after birth. Such processes play a role in early-childhood visual disorders like congenital strabismus (squinting). "In the long term, the model could even enable us to develop better strategies for treating such illnesses," says Rotter.

But why do the neural networks change their structures in the course of visual experience if nerve cells are already specialized in particular stimuli at the moment the eyes first open? The team found an answer to this question in a parallel study. "In a simulation directly comparing inexperienced and fully developed nerve cell networks, we were able to demonstrate that fully developed networks further strengthen components of a stimulus that carry more information by preferring connections of neurons with the same function," explains Rotter. Therefore, while newborns do indeed have the capacity to process all stimuli when they first open their eyes, their perception is greatly improved through the fine tuning of the nerve cell connections.

University of Tokyo researchers have constructed the atomic model structure of the protein complex that corresponds to the stator (stationary part of a motor that surrounds the rotating part of a motor) of the E. coliflagellar motor for the first time by molecular simulation based on previously published experimental data, and elucidated the mechanism by which ions, including hydrogen ions (protons), are transferred through the stator.

Bacteria such as E. coli and Salmonella swim by rotating flagellar motors and filaments, which highly efficiently utilize the energy originating from the difference in ion concentration between the cell interior and exterior. Among the bacterial flagellar motors, some convert the energy by the permeation of protons through the motor stator, while others utilize sodium ions or multiple ions. However, the atomic structure of the bacterial flagellar motor remained unknown, and the mechanism of ion permeation had not been elucidated in detail.

Project Researcher Nishihara Yasutaka at the Graduate School of Arts and Sciences and Associate Professor Akio Kitao at the Institute of Molecular and Cellular Biosciences constructed a three-dimensional model structure of the protein complex that comprises the flagellar motor stator MotA/B, and found that protons permeate through the transmembrane stator as hydronium ions, inducing a motion similar to a ratchet wrench (ratchet movement) limited to one directional rotation.

Investigation of this type of highly efficient energy conversion mechanism is essential to understand biological mechanisms which can utilize energy efficiently.

A team of scientists from the University of St Andrews has developed a new supercomputer modeling tool for assessing the impact of noise from human disturbance, such as offshore wind development, on marine mammal populations.

The team, led by Professor John Harwood of the School of Biology, has created the interim Population Consequences of Disturbance (PCOD) framework for assessing the consequences of human-induced noise-disturbance on animal populations. The study is published today in the journal Methods in Ecology and Evolution.

Changes in natural patterns of animal behaviour and health resulting from them being disturbed may alter the conservation status of a population if the activity affects the ability of individuals to survive, breed or grow. However, information to forecast population-level consequences of such changes is often lacking.

The project team developed an interim framework to assess impacts when evidence is sparse. Crucially, the model shows how daily effects of being disturbed, which are often straightforward to estimate, can be scaled by the duration of disturbance and to multiple sources of disturbance.

One important application for the PCOD framework is in the marine industry. Many industries use practices that involve the generation of underwater noise. These include shipping, oil and gas exploration, defence activities and port, harbour and renewable energy construction.

For example, offshore wind turbines are installed using a method called ‘pile driving’ – which effectively involves a large hammer driving foundation posts into the seabed – which generates short pulsed sounds every few seconds. The potential risk of injury and/or disturbance to marine mammals during these noise-producing activities has been identified as a key consenting risk for offshore wind projects in UK waters, but many other noise sources are less stringently regulated.

Possible consequences of exposure to underwater noise include: disturbance that could cause marine mammals to either move away or change behaviour, eg, stop feeding, or suffer temporary hearing damage or permanent physical injury. The PCOD model assesses what the longer term and larger scale impacts of these consequences on individual animals are to the population as a whole.

The tool has been designed to use the kind of information that is likely to be provided by developers in Environmental Statements and Habitats Regulations Assessments, and currently covers five key priority species in the UK: bottlenose dolphins, harbour porpoises, minke whales, and harbour and grey seals. However, the approach can be applied to other marine and terrestrial species.

This version of the PCOD model is considered an ‘interim’ one, because it was developed to help manage uncertainty within the current knowledge of marine mammals, where there are limited data available on some of the key information needed.

The research follows on from previous work by the team on developing understanding of how noise might impact marine mammal health.

Lead author Dr Stephanie King, Honorary Research Fellow in the School of Biology, said: “The effects of noise on animal populations are a current global concern for policy-makers. We have developed a novel framework that can be used to broadly forecast the consequences of man-made disturbance on animal populations, which, in principal, can be applied to a range of marine and terrestrial species and different types of disturbance. Our framework represents an important first step towards more informed management decisions within a rigorous and quantitative framework.”

Dr Ian Davies, Renewables and Energy Programme Manager at Marine Scotland Science, who chaired the steering committee for the project, said: “The publication of this model provides a new framework and is a significant step forward in our ability to assess acoustic risks to marine mammals. However, it is very much an interim measure; it is expected that it will be further refined and built upon over time as more evidence becomes available. The interim PCOD model is a novel tool that will allow further insight into the potential impacts of disturbance on marine mammal populations. For now, it’s important that renewable energy project developers considering using the Interim PCOD approach seek advice from the SNCBs (Statutory Nature Conservation Bodies)and/or regulators at an early stage.”